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Superscript is seeking a Lead Data Engineer to own the data platform, ensuring it powers BI, underwriting models, ML predictions, and data products at scale. You will define the architectural vision, design end-to-end…
Fospha, a world-leading measurement platform for online retail, invites a Core Data Engineer to design, build and optimise data pipelines, data models, and governance across analytics and ML workflows in London. You…
As a Senior Data Engineer, you will play a key role in building and maintaining production‑ready data and machine‑learning systems that support critical business decisions. You’ll work acrossthe full lifecycle, from…
As Lead Data Engineer at Superscript, you’ll be the technical and strategic owner of our data platform, the foundation that powers everything from business intelligence and underwriting models to machine learning…
is dedicated to building the world's most powerful measurement solution for online retail. For over a decade, we've helped teams make smarter decisions with full-funnel marketing insights, forecasting, and…
Leads the technical direction of a scalable big-data platform: designs and deploys real-time and batch pipelines covering ingestion, transformation, storage, and governance to enable analytics and AI features, while evaluating tools and mentoring engineering teams.
Data Platform Engineer (posted via The BDPN for Chainalysis) in London designing, building, and optimizing scalable cloud data platforms with a focus on real-time streaming: creating CI/CD pipelines, integrating data clouds with databases, and enforcing observability and governance. Core stack: AWS, Terraform, Kafka, Flink, Spark.
Principal Data Engineer who sets technical direction for Anaplan's data platform: designing and shipping scalable batch and real-time pipelines, data lakes/warehouses, and AI-ready storage (vector, NoSQL, document) using Spark, Kafka, Airflow, Snowflake, and cloud infrastructure, while mentoring engineers.
Data Engineer on Chainalysis's Data Cloud team in London, designing and optimizing scalable cloud-native data platforms with a focus on streaming data processing. Day-to-day work spans AWS infrastructure, Terraform automation, CI/CD pipelines, and lakehouse tooling like Kafka, Flink, Spark, Databricks, DBT, and Airflow.
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